Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing | Paper Citation Record

Observation 0f4c0b23-766f-4136-8596-0cc7b4a670af · outbound

This paper cites GPT-4 Technical Report.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing GPT-4 Technical Report

Reference 1

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This paper cites OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models

Reference 2

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This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 3

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This paper cites ACM Manag.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing ACM Manag

Reference 4

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Observation b9a306ae-37f4-4f6d-94f1-bf4bb512a313 · outbound

This paper cites InProceedings of the IEEE/CVF International Conference on Computer Vision(2021), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the IEEE/CVF International Conference on Computer Vision(2021), pp

Reference 5

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This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 6

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Observation 55881563-ae3c-497c-a121-008f9c3b234b · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 7

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Observation fd0fbf6c-7730-4c1f-a7d3-c16f821c11d6 · outbound

This paper cites InInternational Conference on Learning Representations(2021).

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InInternational Conference on Learning Representations(2021)

Reference 8

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Observation 9980e07e-a04d-45d6-a296-181c4f561d48 · outbound

This paper cites R., and Smith, H.Applied Regression Analysis, 3 ed.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing R., and Smith, H.Applied Regression Analysis, 3 ed

Reference 9

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This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 10

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Observation fef7a215-2854-410a-863d-b32ffb5276cc · outbound

This paper cites InProceedings of the 41st International Conference on Machine Learning(2024), vol.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 41st International Conference on Machine Learning(2024), vol

Reference 11

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Observation 875227f0-31f8-44df-9b21-f86cad3dee62 · outbound

This paper cites In2025 USENIX Annual Technical Conference (USENIX ATC 25)(2025), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In2025 USENIX Annual Technical Conference (USENIX ATC 25)(2025), pp

Reference 12

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Observation 17ef0280-4ed0-449c-afc9-ed2c739bd391 · outbound

This paper cites InInternational Conference on Learning Representations (2024), B.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InInternational Conference on Learning Representations (2024), B

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.961424Z

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This paper cites InProceedings of the 42nd International Conference on Machine Learning(13–19 Jul 2025), A.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 42nd International Conference on Machine Learning(13–19 Jul 2025), A

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.090864Z

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Observation 04acdaa5-28fb-49f3-8367-3044b0c53a20 · outbound

This paper cites Gemini 2.5: Pushing the frontier with ad- vanced reasoning, multimodality, long context, and next generation agentic capabilities.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Gemini 2.5: Pushing the frontier with ad- vanced reasoning, multimodality, long context, and next generation agentic capabilities

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.002701Z

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Observation e65d8679-09fe-47ac-ac55-e92cfef0c9c5 · outbound

This paper cites V., Joulin, A., and Misra, I.Imagebind: One embedding space to bind them all.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing V., Joulin, A., and Misra, I.Imagebind: One embedding space to bind them all

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.052947Z

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Observation e904474f-c95f-4cfb-84e6-bc96ed6cfc25 · outbound

This paper cites In16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)(2022), USENIX Association, pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)(2022), USENIX Association, pp

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.105575Z

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Observation 3da091b5-4828-440e-817d-360bd073bda1 · outbound

This paper cites InProceedings of the 2025 USENIX 13 Wang et al.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 2025 USENIX 13 Wang et al

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.049151Z

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Observation 8d79e76c-bbbf-4d29-82da-caa65795eddb · outbound

This paper cites M., and Porikli, F.Distilling multi-modal large language models for autonomous driving.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing M., and Porikli, F.Distilling multi-modal large language models for autonomous driving

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.966566Z

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Observation f68e850c-0a7e-40b6-91aa-546eca0a36c7 · outbound

This paper cites In21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)(2024), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)(2024), pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.112059Z

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Observation 342f2835-c2b4-4430-8d97-39076768f17b · outbound

This paper cites GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:53:24.782412Z

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Observation 710c3465-ff4c-48ac-9417-9555f76bf3ff · outbound

This paper cites InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(2024).

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(2024)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.873735Z

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Observation 8f78167b-b9ea-49a8-a837-4fb549f3fcbc · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.064207Z

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Observation 5f9e6990-7dce-4e61-9bc6-e71d7d65960f · outbound

This paper cites R., Chen, T., and Jia, Z.Graphpipe: Improving performance and scalability of dnn training with graph pipeline parallelism.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing R., Chen, T., and Jia, Z.Graphpipe: Improving performance and scalability of dnn training with graph pipeline parallelism

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.112605Z

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Observation 1fb65cfa-5a91-43d6-9dfb-c87bd92f75b4 · outbound

This paper cites J., Pertsch, K., Karamcheti, S., Xiao, T., Balakrishna, A., Nair, S., Rafailov, R., Foster, E.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing J., Pertsch, K., Karamcheti, S., Xiao, T., Balakrishna, A., Nair, S., Rafailov, R., Foster, E

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.053258Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b30d4ae0-bb9f-489e-8ec3-df5dce41a457 · outbound

This paper cites Efficient Sequence Packing without Cross-contamination: Accelerating Large Language Models without Impacting Performance.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Efficient Sequence Packing without Cross-contamination: Accelerating Large Language Models without Impacting Performance

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:53:24.704147Z

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Observation cbd6dd5c-3a31-401a-960b-fdc2aec1478c · outbound

This paper cites Megrez-omni technical report.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Megrez-omni technical report

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.049386Z

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Observation 442c23a1-c1ce-4b8c-b020-79353d910f77 · outbound

This paper cites Sequence Parallelism: Long Sequence Training from System Perspective.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Sequence Parallelism: Long Sequence Training from System Perspective

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:53:24.750202Z

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Observation 5d78bb56-6993-4079-9bfa-664fc33b3238 · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:53:24.713723Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1aa67e9a-0fda-49db-bfb6-e6f8f068fc8d · outbound

This paper cites Journal of Manufacturing Systems 85(2026), 531–556.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Journal of Manufacturing Systems 85(2026), 531–556

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.101861Z

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Observation e242fd83-d0f5-402d-a821-2da85a2281e4 · outbound

This paper cites J.Visual instruction tuning.Ad- vances in neural information processing systems 36(2023), 34892–34916.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing J.Visual instruction tuning.Ad- vances in neural information processing systems 36(2023), 34892–34916

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.807343Z

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Observation e8a2c561-6f00-4f65-84aa-fb832ae2a88f · outbound

This paper cites InThe Twelfth International Conference on Learning Representations(2024).

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InThe Twelfth International Conference on Learning Representations(2024)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.974903Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e310f04a-6116-4a6b-a3ad-cf50d7278c41 · outbound

This paper cites Ola: Pushing the Frontiers of Omni-Modal Language Model.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Ola: Pushing the Frontiers of Omni-Modal Language Model

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:53:24.776257Z

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Observation b5e68b2a-9b4d-457c-b190-116cbb317852 · outbound

This paper cites InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2024).

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2024)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.998848Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f8c5010a-4fa9-4637-b3b0-85092755b591 · outbound

This paper cites InProceedings of the 32nd ACM International Conference on Multimedia(2024), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 32nd ACM International Conference on Multimedia(2024), pp

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.947618Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3dee6a01-34db-45ef-afff-805e92e3fb21 · outbound

This paper cites Edge ai software market worth 8 .89 billion by 2031.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Edge ai software market worth 8 .89 billion by 2031

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.076143Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 191c8556-e3be-4981-af30-f46c1020454e · outbound

This paper cites Kimi K2.5: Visual agentic intelligence.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Kimi K2.5: Visual agentic intelligence

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.941045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 223f865f-cf55-4a29-b0d3-c20b66f8db4c · outbound

This paper cites R., Ganger, G.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing R., Ganger, G

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.060777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a13f05e1-d17d-4971-b431-3c1fbb5f09dd · outbound

This paper cites Multi-instance gpu user guide.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Multi-instance gpu user guide

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.023718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 906b7024-296d-4ba4-8f33-05297b3af9e2 · outbound

This paper cites Cuda c++ programming guide.https://docs.nvidia.com/cu da/cuda-c-programming-guide/.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Cuda c++ programming guide.https://docs.nvidia.com/cu da/cuda-c-programming-guide/

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.100467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ed4cf8f5-2bbd-4232-9803-c8ba74dad53a · outbound

This paper cites Cuda c++ programming guide: Green contexts.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Cuda c++ programming guide: Green contexts

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.986872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4aaa0ad8-f83b-4ba4-8d2b-eba9826d3ec7 · outbound

This paper cites Cuda multi-process service (mps) overview.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Cuda multi-process service (mps) overview

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.980227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7c681b54-5fa9-454e-982e-31710e0dfa26 · outbound

This paper cites NVIDIA Corporation.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing NVIDIA Corporation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.001748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6ef0d139-9eb2-47bc-896e-34b0daf5199e · outbound

This paper cites [47]Perron, L., and Furnon, V.Or-tools.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing [47]Perron, L., and Furnon, V.Or-tools

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.096483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b9037995-4c75-4a91-83f4-3cc3dac9f115 · outbound

This paper cites Qwen3.5-397B-A17B model card.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Qwen3.5-397B-A17B model card

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.094367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1e65bb7b-7c1b-4901-b624-fef3af30fae0 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.107797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9b6ceb3c-c62a-4fd9-bd4b-5b8014491933 · outbound

This paper cites Y., Awan, A.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Y., Awan, A

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.019564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1e62908d-d712-4e6f-bcb0-e7a5bf2841c1 · outbound

This paper cites In Advances in Neural Information Processing Systems(2021), vol.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In Advances in Neural Information Processing Systems(2021), vol

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.995243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 74d98cf1-ce93-4a53-9714-dd51981bd49e · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.085673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5096095e-c598-41c0-a768-418f038aa746 · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:53:24.772712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 911744e7-906f-4331-a196-7b1251abe96d · outbound

This paper cites S., Shen, H., and Iyer, A.USHER: Holistic interference avoidance for resource optimized ML inference.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing S., Shen, H., and Iyer, A.USHER: Holistic interference avoidance for resource optimized ML inference

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.068028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0d6be196-fb8d-4f60-9466-af1adde6c71c · outbound

This paper cites InComputer Vision – ECCV 2024 (2024), Springer, pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InComputer Vision – ECCV 2024 (2024), Springer, pp

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.098076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 345d1ffd-e3f1-4982-ac04-2019f664c61e · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.074766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4393f1f3-7f1a-455d-affb-c56faa18fc47 · outbound

This paper cites InProceedings of the Nineteenth European Conference on Computer Systems(2024), EuroSys ’24, Association for Computing Machinery, pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the Nineteenth European Conference on Computer Systems(2024), EuroSys ’24, Association for Computing Machinery, pp

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.040875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1ca9261b-e5b8-4b82-930f-b60afa9789dc · outbound

This paper cites Qwen3.5-Omni Technical Report.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Qwen3.5-Omni Technical Report

Reference 55

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:53:24.780521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8197569d-d081-4009-9ad2-6b134008d9c2 · outbound

This paper cites InProceedings of the European Conference on Computer Vision(2020), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the European Conference on Computer Vision(2020), pp

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.044999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 05cf90db-2912-4170-a39b-329a813676db · outbound

This paper cites On-device multimodal ai market report 2026.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing On-device multimodal ai market report 2026

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.061168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation df581536-712b-47ef-9581-3b0c550948a2 · outbound

This paper cites InProceedings of The 8th Conference on Robot Learning(06–09 Nov 2025), P.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of The 8th Conference on Robot Learning(06–09 Nov 2025), P

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.990523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 41d8c289-3f9d-47c8-b5df-ae4eaf9ad74c · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:53:24.756725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 211c31dd-86ab-4459-ad31-0a4f39aecd4f · outbound

This paper cites A practitioner's guide to real-world continual multimodal pretrain- ing.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing A practitioner's guide to real-world continual multimodal pretrain- ing

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.970702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e5e817da-3eb2-4358-80a6-a2cac04eae43 · outbound

This paper cites In2024 USENIX Annual Technical Conference (USENIX ATC 24)(Santa Clara, CA, July 2024), USENIX Association, pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In2024 USENIX Annual Technical Conference (USENIX ATC 24)(Santa Clara, CA, July 2024), USENIX Association, pp

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.843242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3e03d369-085c-42b7-a6e7-03d7ad97c0b4 · outbound

This paper cites InProceedings of the 21st European Conference on Computer Systems (2026), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 21st European Conference on Computer Systems (2026), pp

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.962817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ae228ff4-7e46-47a5-9cce-e0a35acb64f6 · outbound

This paper cites Spindle: Efficient Distributed Training of Multi-Task Large Models via Wavefront Scheduling.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Spindle: Efficient Distributed Training of Multi-Task Large Models via Wavefront Scheduling

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:53:24.786376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c3378f1a-18e8-40ef-b2bf-a4522c4bec60 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.064681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2b0a1f72-a0db-4eb3-ad32-6a3b38615e43 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 65

Resolution: parse uncertain; raw_fallback, observed 2026-05-20T07:53:25.077961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5a70decd-2eec-4663-92d7-f37a4ff40e46 · outbound

This paper cites P., Huang, W.-C., Li, Y., Fang, L., W ang, Z., and Yu, P.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing P., Huang, W.-C., Li, Y., Fang, L., W ang, Z., and Yu, P

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.032207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d40919a0-dd80-4da6-b544-c28acfcc57cc · outbound

This paper cites K., Li, Z., and Zhao, H.Drivegpt4: Interpretable end-to-end autonomous driving via large language model.IEEE Robotics and Automation Letters 9, 10 (2024), 8186–8193.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing K., Li, Z., and Zhao, H.Drivegpt4: Interpretable end-to-end autonomous driving via large language model.IEEE Robotics and Automation Letters 9, 10 (2024), 8186–8193

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.015552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fab823d6-c723-4fbc-9ae5-07deab394a7d · outbound

This paper cites InPro- ceedings of the 21st European Conference on Computer Systems(2026), pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InPro- ceedings of the 21st European Conference on Computer Systems(2026), pp

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.838659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3c18d74e-ecc1-40d3-8768-6f10aac8339c · outbound

This paper cites arXiv.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing arXiv

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:53:24.734817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4485454d-ed96-4f5c-b808-58932d4f86c6 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.108814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4ad5cc40-29fc-4006-a68d-98e82f06d905 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:25.045246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 798c9baf-71e4-41d1-b5cf-698ef61e3501 · outbound

This paper cites InProceedings of Machine Learning and Systems(2020).

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of Machine Learning and Systems(2020)

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.015238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 48c67e25-3b1d-427d-8a39-c5c5eefc2928 · outbound

This paper cites IEEE access 8(2020), 58443–58469.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing IEEE access 8(2020), 58443–58469

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.067626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d91282b1-6c05-42fc-9146-053fe12c0207 · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:24.988276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 89b2b128-5e3a-4137-9a56-7c2235824c62 · outbound

This paper cites In2025 USENIX Annual Technical Conference (USENIX ATC 25)(2025), USENIX Association, pp.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing In2025 USENIX Annual Technical Conference (USENIX ATC 25)(2025), USENIX Association, pp

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.028185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d6069609-df3d-4245-9b4b-8149faef71fb · outbound

This paper cites an unresolved cited work.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-05-20T07:53:24.829857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7fa01068-09ce-4d3c-bb26-3217a79f6569 · outbound

This paper cites InProceedings of the 41st International Conference on Machine Learning(2024), vol.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing InProceedings of the 41st International Conference on Machine Learning(2024), vol

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.041158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c963b174-7075-4b71-9327-3b587e3615d9 · outbound

This paper cites P., Gonzalez, J.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing P., Gonzalez, J

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:25.083602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a93e5057-54bf-49f3-adb8-e5c1e1f13d38 · outbound

This paper cites R., Salazar, G., Ryoo, M.

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing R., Salazar, G., Ryoo, M

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T07:53:24.994467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers